Chapter 1: Business Analytics for Managers
Chapter 2: Descriptive Analytics
Chapter 3: Prediction Modelling
Chapter 4: Time Series Analysis
Chapter 5: Neural Networks and Deep Learning
Chapter 6: Feature Engineering
Chapter 7: Text Analytics
Chapter 8: Image Analysis
Chapter 9: Prescriptive Analytics: Optimization and Modelling
Chapter 10: Big Data Management and Technologies
Chapter 11: Supply Chain Analytics
Chapter 12: CRM & Marketing Analytics
Chapter 13: Financial Analytics
Chapter 14: Human Resources Analytics
Chapter 15: Manufacturing Analytics
With the improvements in collecting, storing and processing data, extracting valuable information from processes has become vital for businesses in a competitive environment. Business analytics are the collection of tools that enables creating business value by gaining insight and information from data. The main subject of the book is to explain concepts and techniques for business analytics and demonstrate them on real life applications for both managers and practitioners. The main feature of this book is to illustrate how machine learning and optimization techniques are used to implement intelligent business automation systems. Problems from main business functions such as supply chain, marketing & CRM, financial, manufacturing and human resources are revealed. The aforementioned problems are taken from different decision levels, namely, strategical, tactical and operational. Then models are proposed and solutions are provided in Python. The main benefit of reading the book is providing knowledge for managerial and technological aspects of business analytics for intelligent automation.With the improvements in collecting, storing and processing data, extracting valuable information from processes has become vital for businesses in a competitive environment. Business analytics are the collection of tools that enables creating business value by gaining insight and information from data. The main subject of the book is to explain concepts and techniques for business analytics and demonstrate them on real life applications for both managers and practitioners. The main feature of this book is to illustrate how machine learning and optimization techniques are used to implement intelligent business automation systems. Problems from main business functions such as supply chain, marketing & CRM, financial, manufacturing and human resources are revealed. The aforementioned problems are taken from different decision levels, namely, strategical, tactical and operational. Then models are proposed and solutions are provided in Python. The main benefit of reading the book is providing knowledge for managerial and technological aspects of business analytics for intelligent automation.
Publisher: Springer Cham
Series Title: Springer Series in Advanced Manufacturing